This course includes:
- 4 hours on-demand video
- 1 article
- 1 downloadable resource
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
What you'll learn
- How to install and use Spacy in Python projects
- The basics of natural language processing and how Spacy can be used for various NLP tasks such as tokenization, tagging, parsing, and named entity recognition.
- How to use Spacy's pre-trained models for different languages and how to create custom pipeline components for specific tasks.
- How to work with large datasets and how to optimize the performance of Spacy for large data sets.
- Hands-on experience working with real-world examples and exercises to solidify their understanding of the concepts.
- How to combine Spacy with other popular Python libraries such as pandas, numpy, and scikit-learn for data analysis and machine learning tasks.
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